The battery industry generally lacks a fast and scalable solution for determining the physical condition of batteries in various stages of their manufacture and use, e.g., during research and development, testing, production, bench assembly, and post fabrication and sealing. The current techniques for diagnosing the physical condition of a battery, e.g., employed at-scale, are limited to electrical and thermal techniques, which are recognized as being inaccurate, destructive, and/or unsuitable for battery diagnostics while the battery is in-use. There is a recognized need for scalable and non-destructive diagnostic techniques for accurately monitoring and assessing a battery's internal state in a way that can inform further analyses of the battery's physical condition, including the ability to determine state of charge (SOC), state of health (SOH), quality of construction, defect or failure state, and other physical properties of the battery.
Current techniques used for battery diagnostics may depend on the specific setting in which the battery is under test. For example, alternating current (AC) impedance spectroscopy and high-precision coulometry may be employed in research settings, although in some cases, other techniques such as high-power synchrotron x-ray diffraction (XRD) and x-ray computed tomography (CT) may also be used. In manufacturing environments, the above-noted research-level techniques may be used along with electrical measurements such as direct current (DC) impedance measurements to gauge internal resistance and initial charge-discharge cycling for gauging capacity, but such techniques may be limited to spot checking. Diagnostic tests performed on every cell of a battery under test may be limited to simple electrical and physical measurements (e.g., open circuit voltage).
With the exception of XRD and CT, the above techniques rely on electrical current being applied to the battery under test, which can be destructive to the battery. However, a drawback of XRD and CT techniques is that they are prohibitively slow and expensive at production scales.
Existing battery diagnostic methods that may be available for detecting or monitoring the physical condition of batteries integrated into electronic devices, electric vehicles, grid-scale energy storage, etc., are typically limited to analyses conducted using electrical tools or thermal sensing. However, these existing diagnostic methods are prone to inaccuracies because they provide averaged data over the entire battery and are not helpful for a more detailed understanding of the internal components, defects, composition distribution, etc., of the battery.
Accordingly, there is emerging research in alternative approaches for determining the physical conditions of batteries which do not rely on electrical tools. In this regard, it is recognized that batteries store energy in the form of chemical potential, wherein during the storage and release of that energy (i.e., during charging and discharging cycles of the battery, respectively), chemical reactions take place that result in a reorganization of mass and a change in materials properties of the battery, including density, modulus, porosity, and thickness. It is also known that the behavior of sound in a material is fundamentally sensitive to these changes in properties. More specifically, the speed of sound through a material is primarily a function of the elastic moduli and density of the material. Moreover, the acoustic impedance of a material (which, like index of refraction for light, influences how sound behaves when entering and leaving a material) is also a strong function of density and moduli. Therefore, it is possible to study and analyze soundwaves passing through the material (or a sample under test) to detect changes in the properties of the material (or sample), which in turn can provide information regarding the physical condition of the material (or sample). Existing approaches for probing a battery using soundwaves are not seen to be sufficiently accurate, nor are they seen to provide a level of detail which would be useful in determining SOH, SOC, possibility of failures, localized defects, etc., whether or not the battery is in use.
Accordingly, there is a recognized need in the industry for detecting a broader scope of physical quality, defects and failure conditions in batteries, either while the battery is deployed and in use or when the battery is not in use.